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HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)
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HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)

Book Details

Format Hardback or Cased Book
Book Series HBR Guide
ISBN-10 1633695573
ISBN-13 9781633695573
Publisher Harvard Business Review Press
Imprint Harvard Business Review Press
Country of Manufacture GB
Country of Publication GB
Publication Date Apr 3rd, 2018
Print length 256 Pages
Weight 530 grams
Dimensions 15.90 x 23.60 x 2.40 cms
Product Classification: Management decision making
Ksh 6,300.00
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Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to:Identify the metrics you need to measureRun experiments and A/B testsAsk the right questions of your data expertsUnderstand statistical terms and conceptsCreate effective charts and visualizationsAvoid common mistakes

Don''t let a fear of numbers hold you back.

Today''s business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?

Whether you''re working with data experts or running your own tests, you''ll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.

You''ll learn how to:

  • Identify the metrics you need to measure
  • Run experiments and A/B tests
  • Ask the right questions of your data experts
  • Understand statistical terms and concepts
  • Create effective charts and visualizations
  • Avoid common mistakes


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